Fig. 1: Benefits of adaptive experimental design.
From: A Bayesian active learning platform for scalable combination drug screens
a, b Traditional approaches to combination studies entail exhaustive enumeration of a small library or random subsampling of a large library. In either case, the resulting models generally are not powerful enough to find clinically relevant discoveries. c Adaptive experimental design allows exploration of a large library. By focusing on the most informative experiments, one can create a powerful model that is capable of finding clinically relevant discoveries. Created in BioRender. Tansey, W. (2024) BioRender.com/k20w361.
